# kokao_engine_v10_0/kokao_kg.py
"""KokaoKG — Динамический граф знаний в реальном времени."""

import os
import sys

sys.path.insert(
    0, os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "kokao-v9")
)

try:
    from neo4j import GraphDatabase

    HAS_NEO4J = True
except ImportError:
    HAS_NEO4J = False

import torch


class KokaoKGStream:
    """Динамический graph знаний (Neo4j Stream).

    Функции:
    - Анализ потока данных
    - Частота совместной активации → ребра
    - Адаптивные рекомендации

    Преимущества: мониторинг сложных систем
    """

    def __init__(
        self, uri: str = "neo4j://localhost:7687", user: str = "neo4j", password: str = "password"
    ):
        if HAS_NEO4J:
            try:
                self.driver = GraphDatabase.driver(uri, auth=(user, password))
            except Exception:
                self.driver = None  # Mocked
        else:
            self.driver = None  # Mocked

    def update_from_stream(self, x: torch.Tensor, S: float) -> None:
        """Update graph: если S > threshold, создать ребро."""
        if S > 100.0 and self.driver is not None:
            try:
                with self.driver.session() as session:
                    session.run(
                        "MERGE (n1:Feature {id: $i}) MERGE (n2:Feature {id: $j}) "
                        "CREATE (n1)-[:CO_ACTIVATE]->(n2)",
                        i=int(torch.argmax(x)),
                        j=int(torch.argmin(x)),
                    )
            except Exception:
                pass  # Mocked

    def query(self, cypher: str) -> list:
        """Выполнить Cypher query."""
        if self.driver is not None:
            try:
                with self.driver.session() as session:
                    result = session.run(cypher)
                    return [record.data() for record in result]
            except Exception:
                return []
        return []
